Development of a Digital twin for Autonomous Driving

Over the last few years, the “simulation hypothesis” has become a significant factor when it comes to testing of autonomous vehicles. A digital twin is a software representation of a physical system with abstractions necessary to bring real world behavior into simulations. This is a cost-effective way to generate data and test various autonomous driving functionalities. Within the research project BEINTELLI we develop a scalable software solution for our vehicle, edge and cloud infrastructure.

The aim of the master thesis is to create accurate representation of our assets such as the test track and test vehicles for virtual simulation. This includes research & development about generation of synthetic data from vehicle & edge infrastructure for a V2V or V2X use-case. The implementation should be optimized based on the limitations of the target platform.

Prerequisites

  • Good knowledge in Unity, Blender and optional experiences with ROS
  • Basic knowledge about Digital twins
  • Basic experience with autonomous driving simulators (LGSVL, CARLA or similar simulators)
  • PS: Concrete tasks will be formulated based on interview & your interests

Literature

  • Marai, O., Taleb, T. and Song, J., 2021. Roads Infrastructure Digital Twin: A Step Toward Smarter Cities Realization. IEEE Network, 35(2), pp.136-143.
  • Steinmetz, C., Schroeder, G., Rettberg, A., Rodrigues, R. and Eduardo Pereira, C., 2021. Enabling and supporting car-as-a-service by digital twin modeling and deployment. 2021 Design, Automation in Europe conference.

Application

We are looking forward to receiving your PDF application. Please send your application with the following documents:

  • Current transcript of records
  • Curriculum vitae in tabular form